Testing that runs itself
Software testing is no longer a manual checkpoint - it is an autonomous pipeline. BetterQA builds and operates agentic QA systems: AI agents that plan test strategies, generate test cases, execute them across environments, and triage failures without waiting for a human to click "run."
From test automation to autonomous testing
Traditional test automation requires humans to write scripts, maintain them, analyze results, and decide what to test next. Agentic QA inverts this: AI agents observe your codebase, understand changes, generate appropriate tests, run them, interpret failures, and report only what matters.
The difference is not incremental - it is architectural. Your QA team shifts from "running tests" to "governing quality."
- Human writes every test
- Manual maintenance burden
- Fixed test suites
- Results require interpretation
- Coverage gaps go unnoticed
- AI generates tests from code
- Self-healing selectors
- Dynamic test selection
- Intelligent failure triage
- Coverage actively monitored
27001
Type II
Ready
The 7-Step Agentic Pipeline
Code Change Detection
Agent monitors repository for commits, PRs, and deployments. Understands what changed and its potential impact.
Impact Analysis
Maps code changes to affected features, APIs, and user flows. Prioritizes what needs testing.
Test Generation
AI generates new test cases for changed code. Updates existing tests. Removes obsolete ones.
Parallel Execution
Runs tests across browsers, devices, and environments simultaneously. Scales elastically.
Intelligent Triage
Classifies failures: real bugs vs. flaky tests vs. environment issues. Groups related failures.
Smart Routing
Routes bugs to the right team/person based on code ownership and expertise. Creates tickets automatically.
Continuous Learning
Agent learns from feedback: which tests are valuable, which failures were false positives, what patterns matter.
BetterQA's Agentic QA Tools
BugBoard
AI-powered test management that generates test cases from requirements, analyzes release readiness, and creates bugs from screenshots. Integrates with your CI/CD via MCP protocol.
- Generate test cases from PRD or user stories
- AI bug creation from screenshots
- Release readiness scoring
- MCP server for Claude/agent integration
bugboard.create_bug_from_screenshot()
→ AI analyzes visual + context
→ Generates title, steps, severity
→ Creates ticket in your tracker
Flows
Record browser tests with Chrome extension, execute them anywhere. Self-healing selectors adapt to UI changes. Data-driven testing from single recordings.
- Chrome extension for visual recording
- AI-powered selector healing
- Convert recordings to data-driven tests
- Parallel execution on any browser grid
flows.run_suite("checkout")
→ Detects broken selectors
→ Auto-fixes using AI
→ Continues execution
Security Toolkit
V4 Maximum Coverage AI security scanning. SAST, SCA, DAST, and secrets detection with cross-pollination between agents for comprehensive vulnerability discovery.
- Multi-agent security scanning
- Attack chain analysis
- Remediation code generation
- OWASP Top 10 coverage
security.scan(target, coverage="maximum")
→ SAST + SCA + DAST agents
→ Cross-pollinate findings
→ Attack chains + remediation
Why Companies Switch to Agentic QA
Ship Without Waiting for QA
Tests run automatically on every commit. No more "waiting for QA to finish." Deploy when code is ready - the pipeline validates continuously.
Coverage That Grows Itself
AI generates tests for new code automatically. Coverage increases with every PR. No more coverage debt accumulating in corners of your codebase.
QA Team Does QA, Not Maintenance
Your QA engineers focus on exploratory testing, edge cases, and quality strategy - not fixing broken selectors and updating test data.
Common Questions
Get Your Free Agentic QA Assessment
We'll analyze your current testing setup and show you exactly where autonomous testing would have the biggest impact.